Biblio

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PhD Thesis
Hazan, A. (2010).  Musical Expectation Modelling from Audio: a causal mid-level approach to predictive representation and learning of spectro-temporal events.. Departament de Tecnologies de la Informació i les Comunicacions. 119. Abstract
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Miscellaneous
Salselas, I., Hazan A., Herrera P., & Purwins H. (2008).  The Development of Melodic Representations at Early Age: Towards a Computational Model.. Music, Language and the Mind 2008. Abstract
Master Thesis
Hazan, A. (2006).  Computational Modeling of Expressive Music Performance New Machine Learning Approaches for Dealing With Real-World Data. Abstract
Journal Article
Purwins, P., Herrera P., Grachten M., Hazan A., Marxer R., & Serra X. (2008).  Computational Models of Music Perception and Cognition I: The Perceptual and Cognitive Processing Chain. Physics of Life Reviews. 5(3), 151-168. Abstract
Purwins, P., Grachten M., Herrera P., Hazan A., Marxer R., & Serra X. (2008).  Computational Models of Music Perception and Cognition II: Domain-Specific Music Processing. Physics of Life Reviews. 5(3), 169-182. Abstract
Ramirez, R., Hazan A., Gómez E., Maestre E., & Serra X. (2005).  Discovering Expressive Transformation Rules from Saxophone Jazz Performances. Journal of New Music Research. 34, 319-330. Abstract
Ramirez, R., Hazan A., Maestre E., & Serra X. (2008).  A Genetic Rule-based Expressive Performance Model for Jazz Saxophone. Computer Music Journal. 32, 38-50. Abstract
Coath, M., Denham S. L., Smith L. M., Honing H., Hazan A., Holonowicz P., et al. (2009).  Model cortical responses for the detection of perceptual onsets and beat tracking in singing. Connection Science. 21(2-3), 193-205. Abstract
application/pdf iconCoathEtAl08ConnSciPreprint.pdf
Ramirez, R., & Hazan A. (2006).  A Tool for Generating and Explaining Expressive Music Performances of Monophonic Jazz Melodies. International Journal on Artificial Intelligence Tools. 15, 673-691. Abstract
Hazan, A., Brossier P., Marxer R., & Purwins P. (2009).  What/when causal expectation modelling applied to percussive audio. The Journal of the Acoustical Society of America, vol. 123, issue 5, p. 3800. Abstract
Hazan, A., Marxer R., Brossier P., Purwins H., Herrera P., & Serra X. (2009).  What/when causal expectation modelling applied to audio signals. Connection Science. 21(2-3), 119 – 143. Abstract
Conference Paper
Ramirez, R., & Hazan A. (2005).  An Approach to Expressive Music Performance Modeling. 118th Audio Engineering Society Convention. Abstract
Grachten, M., Marxer R., Hazan A., & Purwins H. (2007).  Attention as musical interplay of bottom-up accents and expectation. GOSPEL Workshop. Abstract
Hazan, A. (2005).  Billaboop real-time voice-driven drum generator. 118th Audio Engineering Society Convention. Abstract
Hazan, A., Herrera P., Marxer R., Grachten M., & Purwins H. (2007).  Computational Modeling of Statistical Learning of Tone Sequences (Poster). International Conference on Cognitive and Neural Systems (ICCNS 2007). Abstract
Marxer, R., Holonowicz P., Hazan A., & Purwins H. (2008).  Dynamical Hierarchical Self-Organization Of Harmonic And Motivic Musical Categories. Acoustics. Abstract
Marxer, R., Holonowicz P., Purwins H., & Hazan A. (2007).  Dynamical Hierarchical Self-Organization of Harmonic, Motivic, and Pitch Categories . Music, Brain and Cognition. Part 2: Models of Sound and Cognition, held at NIPS). Abstract
Hazan, A., Grachten M., & Ramirez R. (2006).  Evolving performance models by performance similarity beyond note-to-note transformations. Abstract
Hazan, A., Brossier P., Holonowicz P., Herrera P., & Purwins H. (2007).  Expectation Along The Beat A Use Case For Music Expectation Models. International Computer Music Conference. Abstract
Ramirez, R., Hazan A., & Maestre E. (2005).  Intra-note Features Prediction Model for Jazz Saxophone Performance. International Computer Music Conference. Abstract
Ramirez, R., & Hazan A. (2004).  Learning Expressive Performance Rules in Jazz.
Ramirez, R., Hazan A., Gómez E., & Maestre E. (2004).  A machine learning approach to expressive performance in jazz standards. ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. Abstract
Ramirez, R., & Hazan A. (2005).  Modeling expressive music performance in jazz. International Florida Artificial Intelligence Research Society Conference. Abstract
Hazan, A., Holonowicz P., Salselas I., Herrera P., Purwins H., Knast A., et al. (2008).  Modeling the Acquisition of Statistical Regularities in Tone Sequences. 30th Annual Meeting of the Cognitive Science Society. Abstract
Hazan, A., Ramirez R., Maestre E., Pérez A., & Pertusa A. (2006).  Modelling Expressive Performance A Regression Tree Approach Based on Strongly Typed Genetic Programming. European Workshop on Evolutionary Music and Art. Abstract
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